River Publishers Series in Conference Proceedings of the Society for Experimental Mechanics Series

Structural Health Monitoring & Machine Learning, Vol. 12
Proceedings of the 43rd IMAC, A Conference and Exposition on Structural Dynamics 2025

Editors:
Brian Damiano, Babak Moaveni, Antonio De Luca, Keith Worden

ISBN: 9788743801573 e-ISBN: 9788743801696

doi: https://doi.org/10.13052/97887-438-0157-3


Structural health Monitoring &. Machine Learning, Volume 12: Proceedings of the 43rd IMAC, A Conference and Exposition on Structural Dynamics, 2025, the twelth volume of twelve from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of the Structural Health Monitoring, including papers on:

  • Bayesian Methods for Model Inference
  • Health Monitoring using dynamic measurements
  • Health Monitoring using Digital Twinning
  • SHM using Machine Learning
  • Case studies of SHM on real-world dynamic systems
  • Other Innovative SHM Methods
autocovariance function, spatiotemporal, redundant, Flange tightness, state monitoring, virtual sensor, SCADA data, Wind Turbine, Prognosis, Structural health monitoring; Domain adaptation

Article 15: Effective Structural Health Monitoring of Rotating Propellers using Asynchronous Neuromorphic Tracking
by Guillermo Toledo, Wyatt Saeger, Fernando Moreu, David Mascarenas, Christian Torres, Jahsyel Rojas
https://doi.org/10.13052/97887-438-0157-3_15


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